Triple
T22239429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB1 |
E549679
|
entity |
| Predicate | hasIssuerSectorClassification |
P116570
|
FINISHED |
| Object | Financials |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Financials | Statement: [DB1, hasIssuerSectorClassification, Financials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIssuerSectorClassification Context triple: [DB1, hasIssuerSectorClassification, Financials]
-
A.
industryOfUnderlyingIssuer
Indicates the industry sector to which the underlying issuer in a financial or contractual arrangement belongs.
-
B.
hasGICSsector
Indicates that an entity is classified as belonging to a particular Global Industry Classification Standard (GICS) sector.
-
C.
hasMarketSector
chosen
Indicates that an entity operates within, is associated with, or belongs to a particular market sector or industry segment.
-
D.
hasInstitutionalSector
Indicates that an entity is associated with, classified under, or belongs to a particular institutional sector within an economic, organizational, or regulatory framework.
-
E.
isSectorSpecific
Indicates that something is tailored or restricted to a particular industry or sector rather than being generally applicable.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f132133b908190b0fb32a5ee68e1e6 |
completed | April 28, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69e71b5177d881908f90abde14ada7dc |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:38 p.m.